Classiq vs Scale AI

Scale AI has a disclosed valuation of $29B, while Classiq's valuation is not publicly available, making a direct size comparison difficult. Scale AI employs 1,000 people.

Scale AI has raised more in total funding at $15.9B, compared to Classiq's $63M — a gap of $15.8B. Combined, the two companies have completed 9 known funding rounds.

Scale AI leads with an Awaira Score of 84/100, while Classiq sits at 48/100. That 36-point gap reflects real differences in funding, scale, and traction — it's not a vanity metric.

Classiq was founded by Nir Minerbi in 2020. Scale AI was founded by Alexandr Wang in 2016. Visit each company's profile on Awaira for a full founder biography.

Classiq: Classiq develops quantum computing software that automates the synthesis of quantum circuits from high-level algorithmic descriptions, allowing quantum algorithm developers to specify what computation should be performed without manually designing the low-level quantum gate sequences required to implement it. The Tel Aviv company platform generates optimised quantum circuits for specific hardware backends including IBM, Google, and IonQ quantum processors.\n\nThe company raised approximately $63 million in venture funding including a Series C from investors including HPE, NTT, and HSBC. Classiq targets financial services, pharmaceuticals, and logistics companies investigating quantum computing applications for optimisation, simulation, and machine learning, providing software tools that accelerate quantum algorithm development without requiring deep quantum physics expertise from application developers. The company has partnerships with IBM Quantum and NVIDIA cuQuantum for hybrid classical-quantum workflows.\n\nClassiq competes in the quantum software market alongside Qiskit (IBM), Cirq (Google), and commercial quantum software platforms including 1QBit and QC Ware. The company occupies the abstraction layer between algorithm description and hardware implementation, a segment that becomes increasingly valuable as quantum hardware matures and the bottleneck shifts from physical qubit availability to algorithm development productivity. The long timelines to commercial quantum advantage create both extended runway requirements and extended opportunity windows for quantum software infrastructure companies positioned ahead of hardware maturity. Scale AI: Scale AI is a data infrastructure company founded in 2016 that specializes in data labeling and annotation services for artificial intelligence model development. The company provides managed workforce solutions and software platforms that enable organizations to prepare high-quality training data at scale. Scale AI's core offerings include data labeling, model evaluation, data generation, and managed workforce services across computer vision, natural language processing, and other AI domains. The company serves enterprise customers across automotive, defense, technology, and other sectors requiring large-scale data annotation for machine learning applications. Notable use cases include autonomous vehicle development, where precise labeled data is critical for training perception systems. Scale AI operates a hybrid model combining software automation with human-in-the-loop annotation capabilities. With a Series F valuation of $13.8 billion and total funding of $1.6 billion, Scale AI represents one of the highest-valued data infrastructure companies in the AI stack. The company competes in the data labeling market alongside firms like Labelbox, Snorkel AI, and various in-house solutions deployed by large technology companies. Its growth trajectory reflects increasing enterprise demand for quality training data as AI model development accelerates. Scale AI's positioning emphasizes enterprise-grade reliability, security, and quality assurance in data preparation workflows. Scale AI has achieved unicorn valuation by solving the critical bottleneck of high-quality labeled data production at enterprise scale.

Scale AI got there first, launching in 2016 — that's 4 years of extra runway. Classiq didn't arrive until 2020. In AI, that kind of head start means more training data, deeper customer relationships, and a bigger talent moat.

Classiq has about 1-50 employees; Scale AI has about 1,000. A bigger team usually means more revenue or heavier VC backing, but in AI, small teams can build at massive scale.

Yes — they're direct rivals. Both Classiq and Scale AI compete in AI Infrastructure, targeting many of the same buyers. If you're evaluating one, you should be looking at the other.